{"title":"An approach for space registration based on support vector machine","authors":"Z. Niu, Chaowei Chang, Teng Li","doi":"10.1109/ICEDIF.2015.7280177","DOIUrl":null,"url":null,"abstract":"The characteristic and applicability of nonparametric estimation are studied in this paper. A method of space registration based on support vector machine (SVM) is proposed. It is compared with the method of sensor registration based on neural network and the method of generalized least square estimator (GLS) in multi-kind parameters. The results illustrate that the method of space registration based on support vector machine is effective.","PeriodicalId":355975,"journal":{"name":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Estimation, Detection and Information Fusion (ICEDIF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEDIF.2015.7280177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The characteristic and applicability of nonparametric estimation are studied in this paper. A method of space registration based on support vector machine (SVM) is proposed. It is compared with the method of sensor registration based on neural network and the method of generalized least square estimator (GLS) in multi-kind parameters. The results illustrate that the method of space registration based on support vector machine is effective.
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